CN109767074A - Effect comprehensive estimation method is planned in a kind of distribution of high reliability service area - Google Patents
Effect comprehensive estimation method is planned in a kind of distribution of high reliability service area Download PDFInfo
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Abstract
The present invention relates to the distributions of high reliability service area to plan effect comprehensive estimation method, comprising the following steps: step 1) foundation includes the planning effectiveness indicator appraisement system of rule layer and indicator layer two-stage；Step 2 combines different grid structures, electrical equipment type, automatic configuration method and communication building method to determine high reliability service area distribution programme；Step 3) obtains the basic data of distribution planning；Step 4) determines each criterion weight in rule layer；Step 5) determines each index weights in indicator layer；Step 6) determines each index score function；Step 7) obtains comprehensive assessment result.The utility model has the advantages that facilitating distribution planning construction policymaker selects suitable high reliability power supply area distribution programme；Solves the problems such as high reliability power supply area distribution planning effectiveness indicator appraisement system is indefinite, evaluation result is fuzzy.
Description
Technical field
The present invention relates to distribution planning effect comprehensive assessment field more particularly to a kind of high reliability service area distribution planning
Effect comprehensive estimation method.
Background technique
As Urbanization in China is accelerated rapidly, the construction of the high reliability power supply area such as Urban New District, economic development zone
It is like a raging fire.High reliability service area generally A+, A class power supply area range as defined in " distribution network planning designing technique directive/guide "
It is interior, to the economy of power distribution network, safety, reliability and technical there is higher requirement in planning construction.
Currently, having carried out the research to high reliability service area distribution programme with domestic and foreign scholars in industry.
Since the factor that distribution network planning construction is related to is more, the evaluation of high reliability distribution network construction planning effect is referred to for a long time
Mark multiplicity, so that policymaker does not have unified standard when selecting high reliability distribution network construction programme.
Summary of the invention
Present invention aims to overcome that the deficiency of above-mentioned existing issue, a kind of policymaker for distribution planning construction is provided and is existed
Select the high reliability service area distribution planning effect comprehensive assessment side that important foundation is provided when suitable distribution programme
Method combines economy, safety, reliability and technical four criterion, and sets up corresponding index for each criterion, in all directions
The distribution network planning effect for having evaluated high reliability power supply area, is specifically realized by the following technical scheme:
Effect comprehensive estimation method is planned in the high reliability service area distribution, comprising the following steps:
Step 1) foundation includes the planning effectiveness indicator appraisement system of rule layer and indicator layer two-stage；
Step 2) combines different grid structures, electrical equipment type, automatic configuration method and communication building method true
Determine high reliability service area distribution programme；
Step 3) obtains the basic data of distribution planning；
Step 4) determines each criterion weight in rule layer；
Step 5) determines each index weights in indicator layer；
Step 6) determines each index score function；
Step 7) obtains comprehensive assessment result.
The further design of high reliability service area distribution planning effect comprehensive estimation method is, in step 1),
The rule layer includes: economy criterion, security criterion, reliability criterion and technical criterion；The economy criterion
Corresponding economic performance index factor collection, including initial outlay cost, transformation and upgrade cost and operation management cost；
The security criterion corresponds to safe performance indexes set of factors, including safe power supply ability, static voltage security,
Transient security and topological structure fragility；
The reliability criterion corresponds to reliability index set of factors, including average power supply availability ASAI, user averagely stop
Electric duration CAIDI, system System average interruption duration SAIDI and system System average interruption frequency SAIFI；The technical standard
Then correspond to technical indicator set of factors, including the level of IT application, equipment quality level, the strong degree of grid structure and Automated water
It is flat.
The further design of high reliability service area distribution planning effect comprehensive estimation method is, in step 3),
The basic data is to be used to calculate the data of each index value size in the indicator layer under corresponding distribution programme.
The further design of high reliability service area distribution planning effect comprehensive estimation method is, in step 4),
The rule layer weight is calculated using the anti-entropy assessment of DEMATEL-ANP-；
The criterion weight and index weights set use 1-5 scaling law, respectively correspond for it is general it is important, slightly important,
Obvious important, strong important, extremely important 5 basic scales, each basic scale impart respectively corresponding numerical measure 1,
3,5,7,9 assignment is carried out.
High reliability service area distribution plans that the further design of effect comprehensive estimation method is, the step 5)
In, the indicator layer weight is calculated using improved grey model degree of association method, and the improved grey model degree of association method includes: that step a) is determined
Initial weight value
Micro-judgment is made to n evaluation criterion weight for determining target equipped with m expert, composition judges that data arrange, such as
Formula (1):
Step b) determines reference sequences according to formula (2), and weight limit value is selected from each column of X and is used as with reference to weighted value
x0m, form reference data array X0,
X0=[x01,x02,...,x0m] (2)
Step c) seeks each index series X according to formula (3)1,X2,...,XnWith reference data X0Between distance,
Step d) seeks the weight of each index according to formula (4)；
Step e) seeks the normalized weight of each index,
The further design of high reliability service area distribution planning effect comprehensive estimation method is, in step 6),
Each score function plans the curve matching that standards of grading carry out by quadratic polynomial approximating method, to discrete distribution,
Establish each index score function.
The further design of high reliability service area distribution planning effect comprehensive estimation method is, in step 7),
The comprehensive assessment obtains each index scoring the result is that the basic data substitution index score function that distribution in step 3) is planned
As a result, the scoring of each index and corresponding multiplied by weight, obtain each criterion appraisal result, to obtain comprehensive assessment result.
Advantages of the present invention is as follows:
(1) high reliability power supply area distribution planning effect comprehensive estimation method is established, different high reliability have been carried out
Economy, safety, reliability and the technical analysis of effect are planned in power supply area distribution, are facilitated distribution planning construction and are determined
Plan person selects suitable high reliability power supply area distribution programme.
(2) high reliability power supply area distribution planning effectiveness indicator appraisement system is established, with qualitative criteria and quantitative finger
Mark is integrated as principle, takes into account subjectivity and objectivity, solves high reliability power supply area distribution planning effectiveness indicator evaluation
The problems such as system is indefinite, evaluation result is fuzzy.
Detailed description of the invention
Fig. 1 is that effect comprehensive assessment flow chart is planned in distribution.
Fig. 2 is that effectiveness indicator system is planned in distribution.
Specific embodiment
With reference to the accompanying drawing to the further explanation of the technical program.
Such as Fig. 1, effect comprehensive estimation method is planned in the high reliability service area distribution that this implementation example provides, including following
Step:
Step 1) establishes high reliability service area distribution planning effectiveness indicator appraisement system；
Step 2) determines high reliability service area distribution programme；
Step 3) obtains the basic data of distribution planning；
Step 4) determines each criterion weight in rule layer；
Step 5) determines each index weights in indicator layer；
Step 6) determines each index score function；
Step 7) obtains comprehensive assessment result.
Indicator evaluation system includes rule layer and indicator layer two-stage in step 1).Rule layer include economy, safety, can
By property and technical four criterion；Wherein, economy criterion corresponds to economic performance index factor collection, and corresponding indicator layer includes just
Beginning cost of investment, transformation and upgrade cost and operation management cost.Security criterion corresponds to safe performance indexes set of factors, corresponding
Indicator layer includes safe power supply ability, static voltage security, transient security and topological structure fragility.Reliability criterion pair
Reliability index set of factors is answered, corresponding indicator layer includes averagely power availability ASAI, user's System average interruption duration
CAIDI, system System average interruption duration SAIDI and system System average interruption frequency SAIFI.Technical criterion corresponds to technical indicator
Set of factors, corresponding indicator layer include the level of IT application, equipment quality level, the strong degree of grid structure and automatization level.
The high reliability service area distribution programme of the present embodiment is electrically set using the strong grid structure of consideration, high quality
The distribution programme of standby, high automatization level and high information level.
Assignment is carried out between the degree that directly affects mutual Macro demand index, uses C1,C2,C3,C4Respectively represent economy
Property, safety, reliability, technical 4 rule layer indexs can be divided into general, slightly important, obvious weight using 1-5 scaling law
It wants, strong important, extremely important 5 basic scales, imparts corresponding numerical measure 1,3,5,7,9 respectively to be measured,
It obtains influencing relational matrix, as shown in table 2:
2 rule layer Index Influence relational matrix of table
| Scale | C1 | C2 | C3 | C4 |
| C1 | / | 7 | 7 | 7 |
| C2 | 5 | / | 3 | 7 |
| C3 | 5 | 5 | / | 5 |
| C4 | 3 | 3 | 5 | / |
The judgement sequence for removing the criterion under each rule layer is established respectively, and calculates function using the matrix in MATLAB tool
Can, corresponding normalization characteristic vector is calculated, as shown in 3~table of table 6:
The judgment matrix and feature vector of index under 3 economy criterion of table
The judgment matrix and feature vector of index under 4 security criterion of table
The judgment matrix and feature vector of index under 5 reliability criterion of table
The judgment matrix and feature vector of index under 6 technical performance criterion of table
The present embodiment rule layer weight is calculated using the anti-entropy assessment of DEMATEL-ANP-.Wherein, DEMATEL (Decision
Making Trial and Evaluation Laboratory) method, i.e., " decision experiments and evaluation experimental method " screen complexity
The essential element of system, simplied system structure analytic process.While Network Analysis Method (Analytic Network Process,
ANP influencing each other between element and dominance relation) can be fully considered, to solve practical decision problem.Therefore this patent is adopted
With DEMATEL-ANP, the subjective weight of 4 criterion is determined.Entropy assessment is a kind of to can be used for the multipair synthesis as, multi objective and comment
Valence method, evaluation result is mainly according to objective materials, hardly by subjective impact, can largely avoid artificial
The interference of factor.To avoid the occurrence of, index diversity factor sensibility is larger in entropy assessment, leads to occur index mistake when weight distribution
Small extreme case, this patent determine the objective weight of 4 criterion with anti-entropy assessment.
Further, the anti-entropy assessment of DEMATEL-ANP- determines each criterion subjectivity weight according to DEMATEL-ANP method
Set ws={ wsi|1≤i≤n}；According to anti-entropy assessment, the objective weight set w of each criterion is determinedo={ woi|1≤i≤n}；Root
Combining weights set w={ w is obtained according to each criterion subjectivity weight and objective weighti|1≤i≤n}。
Further, DEMATEL-ANP method, it is assumed that the network layer of ANP has n criterion, respectively with C1,C2,…,CnTable
Show, there are dependences between each criterion inside, with yjiExpressiveness Cj(j ≠ i) is for CiSignificance level.Successively with Ci(i
=1,2 ..., n) it is criterion, compare C two-by-twoiRemaining index value in addition to its own, obtains corresponding weight matrix.Root
According to eigenvalue method, obtain with CiFor the weight vectors under criterionWeight matrix is shown in formula
(1):
Under each rule layer, influence relationship is not present on its own in criterion, i.e. matrix diagonals line element is 0, is obtained straight
Meet influence matrix Wd, see formula (2):
To directly affecting matrix WdFinding limit can combined influence matrix, see formula (3):
W=limn→∞(Wd)n (3)
Each row element of the matrix tends to some stationary value, and the non-zero stationary value of final each row is corresponding each
The subjective weighted value w of elementsi, then subjective weight sets are as follows:
ws={ wsi|1≤i≤n} (4)
The anti-entropy assessment, it is assumed that evaluation object m, evaluation index n, metrics evaluation matrix X=(xij)n×m, wherein
xij(i=1,2 ..., n；J=1,2 ..., m) it is index value.The step of anti-entropy assessment seeks index weights is as follows:
The negative entropy for determining each index, as shown in formula (5):
In formula,
The h sought according to above formulai, weight normalized is carried out, w is acquiredoi, as shown in formula (6):
Then objective weight collection are as follows:
wo={ woi|1≤i≤n} (7)
According to criterion difference, the relative importance of subjective and objective weight is also different.If subjective weight and objective weight
Relative importance be expressed as αiAnd βi, the basic thought of associate(d) matrix estimation theory finally calculates the master of each criterion
It sees and objective weight significant coefficient αiAnd βi, formula is such as shown in (8):
Using the relatively important coefficient of the subjective weight set, objective weight set and the subjective and objective weight that have obtained, finally
Combining weights w can be calculatedi, formula is such as shown in (9):
Above-mentioned weight vectors are merged, and diagonal part is filled out into numerical value 0, the side DEMATEL can be obtained
Matrix W is directly affected in methodd, formula is such as shown in (10):
To directly affecting matrix WdFinding limit, obtains its combined influence matrix, and each row element of the matrix tends to be a certain
A stationary value, the non-zero stationary value of final each row are the subjective weighted value of corresponding each element, subjective weight vectors formula
As shown in (11):
ws=[0.3046 0.2419 0.2511 0.2024]T (11)
When determining objective weight, calculated using anti-entropy assessment, first to the initial weight of Macro demand index into
Row assignment finally obtains Primary Judgement Matrix X shown in formula (12).Observation is it is found that each row element of matrix X respectively represents needle
To the weight opinion set of a certain index, each column element respectively represents each expert to all referring to target weight opinion set,
The sum of column element is 1.
Calculated according to formula (5), (6) and (7), can be obtained the objective weight of each index of normalized rule layer to
Measure wo, as shown in formula (13).
w0=[0.2475 0.2484 0.2490 0.2551]T (13)
On the basis of the master of each rule layer index known, objective weight vector, according to formula (8), the combining weights of (9)
Calculation method, the final combining weights vector w of available each indexi, as shown in formula (14).It can be with by weight calculation result
Find out, basic demand, index weights are bigger, and the influence to distribution planning effect is bigger, demonstrate hereinbefore
The reasonability of demand layer structure.Final combining weights effectively combine the subjective information and objective information of index, play
The effect of optimizing index weight.
wi=[0.2773 0.2437 0.2486 0.2304]T (14)
The present embodiment assigns associated weight to each index, as shown in 7~table of table 10.
The expert opinion set of each index under 7 economy criterion of table
The expert opinion set of each index under 8 security criterion of table
The expert opinion set of each index under 9 reliability criterion of table
The expert opinion set of each index under 10 technical performance criterion of table
According to improved grey model degree of association method, solve each index weights in indicator layer, with the weighted value of each index of rule layer into
Row is multiplied, and obtains the weighted value of distribution planning each index of effect, as shown in table 11.
Improved grey model degree of association method sufficiently combines the subjective information and scientific and simple mathematics of expertise judgment value
Model overcomes the defect that traditional grey relational grade analysis method influences in calculating process vulnerable to resolution ratio ρ value, makes
Obtained index weights can not only fully reflect subjective degree, can also reflect subjective degree to a certain extent.It is calculated
Method and steps is as follows:
Step a) determines initial weight value: making experience to n evaluation criterion weight for determining target equipped with m expert and sentences
Disconnected, composition judges that data arrange, such as formula (15):
Step b) determines reference sequences: selecting weight limit value from each column of X and is used as with reference to weighted value, forms reference number
According to column X0。
X0=[x01,x02,...,x0m] (16)
Step c) seeks each index series X1,X2,...,XnWith reference data X0Between distance.
Step d) seeks the weight of each index.
Step e) seeks the normalized weight of each index.
Each index weights of effect are planned in 11 distribution of table
Pointer type is generally divided into profit evaluation model, cost type, ad hoc type three classes, wherein profit evaluation model index with index value increasing
Its big score increases, and cost type index increases with its score of the reduction of index value, and ad hoc type index value is in certain intermediate number
Its score highest when value or subinterval value.Table 12 lists the type and ideal value that each index is planned in distribution, and scoring uses hundred
Tabulation is divided to show.
Recruitment evaluation system pointer type and weight are planned in 12 distribution of table
Reasonable standards of grading are made, that is, are referred to reference to expert opinion according to the difference of pointer type and index ideal value
Mark the corresponding relationship between numerical value and index score.It is as shown in table 13:
The standards of grading of 13 distribution of table planning effectiveness indicator system
Polynomial quadratic polynomial fitting side using MATLAB software, in Curve Fitting Tool tool
Method carries out curve fitting to discrete distribution planning standards of grading, distribution planning index system score function is obtained, such as 14 institute of table
Show:
Effect comprehensive assessment index system score function is planned in 14 distribution of table
In above-mentioned table, according to quadratic polynomial curve-fitting method, establish in distribution planning effect comprehensive assessment system
The score function of each index can further analyze the assessment of distribution planning effect comprehensive assessment system by the standards of grading
As a result.Profit evaluation model and cost type index are all made of the curve matching of quadratic polynomial as each index score function, can satisfy
Corresponding relationship between set index value and scoring before, error difference are smaller.
Basic data is substituted into score function and obtains Jiangsu high reliability power supply area distribution planning effect in conjunction with weight
Fruit appraisal result.Table 15 is that effectiveness indicator assessment result is planned in high reliability power supply area distribution in Jiangsu.
Effectiveness indicator assessment result is planned in 15 Jiangsu high reliability power supply area distribution of table
The high reliability service area distribution planning effect comprehensive estimation method of the present embodiment establishes high reliability service area
Effect comprehensive estimation method is planned in domain distribution, has carried out economy, the peace of different high reliability power supply area distribution planning effects
Quan Xing, reliability and technical analysis facilitate distribution planning construction policymaker and select suitable high reliability power supply area
Distribution programme；High reliability power supply area distribution planning effectiveness indicator appraisement system is established, also simultaneously with qualitative criteria
It is integrated as principle with quantitative target, takes into account subjectivity and objectivity, solves high reliability power supply area distribution planning effect
The problems such as indicator evaluation system is indefinite, evaluation result is fuzzy comprehensively and truly reflects high reliability power supply area distribution planning
The beneficial effect of scheme.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
It for member, can also make several improvements without departing from the principle of the present invention, these improvement also should be regarded as of the invention
Protection scope.
Claims (7)
1. effect comprehensive estimation method is planned in a kind of distribution of high reliability service area, which comprises the following steps:
Step 1) foundation includes the planning effectiveness indicator appraisement system of rule layer and indicator layer two-stage；
It is high that step 2) combines different grid structures, electrical equipment type, automatic configuration method and communication building method to determine
Reliability service area distribution programme；
Step 3) obtains the basic data of distribution planning；
Step 4) determines each criterion weight in rule layer；
Step 5) determines each index weights in indicator layer；
Step 6) determines each index score function；
Step 7) obtains comprehensive assessment result.
2. effect comprehensive estimation method is planned in high reliability service area according to claim 1 distribution, which is characterized in that step
It is rapid 1) in, the rule layer includes: economy criterion, security criterion, reliability criterion and technical criterion；
The economy criterion corresponds to economic performance index factor collection, including initial outlay cost, transformation and upgrade cost and O&M
Management cost；
The security criterion corresponds to safe performance indexes set of factors, including safe power supply ability, static voltage security, transient state
Safety and topological structure fragility；
The reliability criterion corresponds to reliability index set of factors, including average power supply availability ASAI, user averagely have a power failure and hold
Continuous time CAIDI, system System average interruption duration SAIDI and system System average interruption frequency SAIFI；The technical criterion pair
Answer technical indicator set of factors, including the level of IT application, equipment quality level, the strong degree of grid structure and automatization level.
3. effect comprehensive estimation method is planned in high reliability service area according to claim 1 distribution, which is characterized in that step
It is rapid 3) in, the basic data be under corresponding distribution programme in the indicator layer for calculating each index value size
Data.
4. effect comprehensive estimation method is planned in high reliability service area according to claim 1 distribution, which is characterized in that step
It is rapid 4) in, the rule layer weight is calculated using the anti-entropy assessment of DEMATEL-ANP-；
The criterion weight and index weights set use 1-5 scaling law, and it is general important, slightly important, obvious for respectively corresponding
Important, strong important, extremely important 5 basic scales, each basic scale impart respectively corresponding numerical measure 1,3,5,
7,9 assignment is carried out.
5. effect comprehensive estimation method is planned in high reliability service area according to claim 1 distribution, which is characterized in that institute
It states in step 5), the indicator layer weight is calculated using improved grey model degree of association method, and the improved grey model degree of association method includes:
Step a) determines initial weight value
Micro-judgment is made to n evaluation criterion weight for determining target equipped with m expert, composition judges that data arrange, such as formula
(1):
Step b) determines reference sequences according to formula (2), and weight limit value is selected from each column of X and is used as with reference to weighted value x0m, group
At reference data array X0,
X0=[x01,x02,...,x0m] (2)
Step c) seeks each index series X according to formula (3)1,X2,...,XnWith reference data X0Between distance,
Step d) seeks the weight of each index according to formula (4)；
Step e) seeks the normalized weight of each index,
6. effect comprehensive estimation method is planned in high reliability service area according to claim 1 distribution, which is characterized in that step
It is rapid 6) in, each score function is by quadratic polynomial approximating method, the song that carries out to discrete distribution planning standards of grading
Line fitting, establishes each index score function.
7. effect comprehensive estimation method is planned in high reliability service area according to claim 4 distribution, which is characterized in that step
It is rapid 7) in, the comprehensive assessment obtains each the result is that the basic data that distribution in step 3) is planned substitutes into index score function
Index appraisal result, the scoring of each index and corresponding multiplied by weight obtain each criterion appraisal result, to obtain comprehensive assessment knot
Fruit.
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